app data

This paper is the first to explore a recent breakthrough with the
introduction of the High Performance Computing (HPC) industry’s first Intelligence Community Directive (ICD) 503 (DCID 6/3 PL4) certified compliant and secure scale-out parallel file system solution, Seagate ClusterStor™ Secure Data Appliance, which is designed to address government and business enterprise need for collaborative and secure
information sharing within a Multi-Level Security (MLS) framework at Big Data and HPC Scale.

With High Performance Computing (HPC) supercomputer systems that comprise tens, hundreds, or even thousands of computing cores, users are able to increase application performance and accelerate their workflows to realize dramatic productivity improvements.
The performance potential often comes at the cost of complexity. By their very nature, supercomputers comprise a great number of components, both hardware and software, that must be installed, configured, tuned, and monitored to maintain maximum efficiency. In a recent report, IDC lists downtime and latency as two of the most important problems faced by data center managers.

The Open Compute Project, initiated by Facebook as a way to increase computing power while lowering associated costs with hyper-scale computing, has gained a significant industry following. While the initial specifications were created for a Web 2.0 environment, Penguin Computing has adapted these concepts to create a complete hardware ecosystem solution that addresses these needs and more. The Tundra OpenHPC system is applicable to a wide range of HPC challenges and delivers the most requested features for data center architects.

Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers.
Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.

Although high-performance computing (HPC) often stands apart from a typical IT infrastructure—it uses highly specialized scale-out compute, networking and storage resources—it shares with mainstream IT the ability to push data center capacity to the breaking point. Much of this is due to data center inefficiencies caused by HPC storage growth.
The Seagate® ClusterStor™ approach to scale-out HPC storage can significantly improve data center efficiency. No other vendor solution offers the same advantages.

View this demo to learn how IBM Platform Computing Cloud Service running on the SoftLayer Cloud helps you: quickly get your applications deployed on ready-to-run clusters in the cloud; manage workloads seamlessly between on-premise and cloud-based resources; get help from the experts with 24x7 Support; share and manage data globally; and protect your IP through physical isolation of bare metal hardware assets.

View this series of short webcasts to learn how IBM Platform Computing products can help you ‘maximize the agility of your distributed computing environment’ by improving operational efficiency, simplify user experience, optimize application using and license sharing, address spikes in infrastructure demand and reduce data management costs.

HPC and technical computing environments require the collection, storage,and transmission of large-scale datasets. To meet these demands, datacenter architects must consider how increasing storage capacity over time will affect HPC workloads, performance, and system availability.
While many enterprises have looked to scale-up NAS to meet their storage needs, this approach can lead to data islands that make it difficult to share data. Distributed, scale-out storage was developed to get around the technology limitations of scale-up NAS architectures.

The term “Big Data” has become virtually synonymous with “schema on read” (where data is applied to a plan or schema as it is ingested or pulled out of a stored location) unstructured data analysis and handling techniques like Hadoop. These “schema on read” techniques have been most famously exploited on relatively ephemeral human-readable data like retail trends, twitter sentiment, social network mining, log files, etc.
But what if you have unstructured data that, on its own, is hugely valuable, enduring, and created at great expense? Data that may not immediately be human readable or indexable on search? Exactly the kind of data most commonly created and analyzed in science and HPC. Research institutions are awash with such data from large-scale experiments and extreme-scale computing that is used for high-consequence

Administrators, engineers and executives are now tasked with solving some of the world’s most complex challenges. This could revolve around advanced computations for science, business, education, pharmaceuticals and beyond. Here’s the challenge – many data centers are reaching peak levels of resource consumption; and there’s more work to be done. So how are engineers and scientists supposed to continue working around such high-demand applications? How can they continue to create ground-breaking research while still utilizing optimized infrastructure? How can a platform scale to the new needs and demands of these types of users and applications. This is where HP Apollo Systems help reinvent the modern data center and accelerate your business.

How secure is your company’s network?
The rising frequency of employee network access is fast becoming one of the most prevalent and unmanaged risks to the protection of critical enterprise data. When coupled with increasingly sophisticated cyber-attacks, the possibility of a security breach of enterprise networks becomes more likely.
As one of the world’s leading location platforms in 2018, HERE shares insights and solutions to preventing identity fraud. Discover the latest facts and statistics. Learn more about the use-case of location verification when logging into your company’s network.
Download the infographic from HERE Technologies.

Imagine if you could see deep into the future. And way back into the past, both at the same time. Imagine having visibility of everything that had ever happened and everything that was ever going to happen, everywhere, all at once.
And then imagine processing power strong enough to make sense of all this data in every language and in every dimension. Unless you’ve achieved that digital data nirvana (and you haven’t told the rest of us), you’re going to have some unknowns in your world.
In the world of security, unknown threats exist outside the enterprise in the form of malicious actors, state-sponsored attacks and malware that moves fast and destroys everything it touches. The unknown exists inside the enterprise in the form of insider threat from rogue employees or careless contractors – which was deemed by 24% of our survey respondents to pose the most serious risk to their organizations. The unknown exists in the form of new devices, new cloud applications, and new data. The unk

The Cornerstone of Financial Control
Time equals money. Time plus data equals control.
All professionals, whether in management, consulting,
engineering, or accounting, must be confident that their
value is reflected in their bottom line. One of the primary
factors driving that compensation is the amount of time
spent on a particular subject or client. But too often front
line earners at those firms don’t provide the clean, data-rich
timesheets needed to accurately gauge the effort required
by each project.

When it comes to cybersecurity, you can only defend what you can see. Organizations continue to suffer breaches, oftentimes because they do not have continuous, real-time visibility of all their critical assets. With more data and applications moving to the cloud, IoT and other emerging technologies, the attack surface continues to expand, giving adversaries more blind spots to leverage.
Watch a webinar with SANS where we examine how to:
Discover, classify and profile assets and network communications
Detect threats and decode content in real-time at wire speed
Hunt for unknown threats via rich, indexable metadata
Alter your terrain and attack surface with deception to slow down attackers
By knowing your cyber terrain and increasing the risk of detection and cost to the adversary, you can gain a decisive advantage.

Personalization runs through every retail interaction, and it has the potential to make or break consumers’ relationship with your brand. But we don’t need to tell you about the importance of personalization. What we do need to talk about is how to get it right. And why email is the best place to start.
Creating a personalized experience in the league of retail pacesetters like Stitch Fix and Sephora is all about bringing together an intimate knowledge of both your customers and your products. This eBook explores what it takes to make that happen, including how to parness product data for retail personalization, what truly relevant experiences look like and how to remove common technology roadblocks to achieving retail relevance.

Machine Learning For Dummies, IBM Limited Edition, gives you insights into what machine learning is all about and how it can impact the way you can weaponize data to gain unimaginable insights. Your data is only as good as what you do with it and how you manage it. In this book, you discover types of machine learning techniques, models, and algorithms that can help achieve results for your company. This information helps both business and technical leaders learn how to apply machine learning to anticipate and predict the future.
You will find topics like:
- What is machine learning?
- Explaining the business imperative
- The key machine learning algorithms
- Skills for your data science team
- How businesses are using machine learning
- The future of machine learning

Discover the four big trends in fleet management being powered by location services. Trends to help you differentiate your solutions and enable transportation companies to overcome their logistical challenges and increase asset utilization. Discover what’s making the biggest impact, together with how, by integrating some of these trends into your solutions, you can position yourself as the service provider of choice in fleet and transportation management solutions. And find out how HERE is delivering features, from comprehensive mapping capabilities and real-time location data, to truck-specific attributes, to help you do just that.
Download the eBook now

On-demand companies rely on fast, accurate and robust mapping and location technologies to provide their users with a superior experience. Find out how real-time, predictive and historical traffic data can be applied to traffic-enabled routing algorithms to influence route calculations and automatically plot multiple routes with waypoints sequencing.
Discover how HERE can help you communicate updated ETAs and provide an optimized experience to your drivers and customers.

Data is the lifeblood of business. And in the era of digital business,
the organizations that utilize data most effectively are also the most
successful. Whether structured, unstructured or semi-structured,
rapidly increasing data quantities must be brought into organizations,
stored and put to work to enable business strategies. Data integration
tools play a critical role in extracting data from a variety of sources and
making it available for enterprise applications, business intelligence
(BI), machine learning (ML) and other purposes. Many organization
seek to enhance the value of data for line-of-business managers by
enabling self-service access. This is increasingly important as large
volumes of unstructured data from Internet-of-Things (IOT) devices
are presenting organizations with opportunities for game-changing
insights from big data analytics. A new survey of 369 IT professionals,
from managers to directors and VPs of IT, by BizTechInsights on
behalf of IBM reveals the challe

The data maturity curve
As companies invest more and more in data access and
organization, business leaders seek ways to extract more
business value from their organization’s data.
92 percent of business leaders say that to compete in the future,
their organization must be able to exploit information much more
quickly than it can today.1
Chief Information Officers (CIO) need solutions that will allow
them to evolve their organization’s approach to data and drive real
value with strategic decisions. This journey can be depicted in
a data maturity curve.

IBM Cloud Private for Data is an
integrated data science, data engineering
and app building platform built on top of
IBM Cloud Private (ICP). The latter is intended
to a) provide all the benefits of cloud
computing but inside your firewall and b)
provide a stepping-stone, should you want
one, to broader (public) cloud deployments.
Further, ICP has a micro-services architecture,
which has additional benefits, which we
will discuss. Going beyond this, ICP for Data
itself is intended to provide an environment
that will make it easier to implement datadriven processes and operations and, more
particularly, to support both the development
of AI and machine learning capabilities, and
their deployment. This last point is important
because there can easily be a disconnect
Executive summary
between data scientists (who often work for
business departments) and the people (usually
IT) who need to operationalise the work of
those data scientists

There can be no doubt that the architecture for analytics has evolved
over its 25-30 year history. Many recent innovations have had significant
impacts on this architecture since the simple concept of a single
repository of data called a data warehouse. First, the data warehouse
appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the
traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had
a substantial effect on the analytical architecture.

IP communications across multiple, sometimes untrusted, networks needs to be normalized, managed and secured. As part of the most cost-effective, easiest to manage line of Session Border Controllers on the market. Read to learn how they can help you.

The most cost effective, easiest to provision, and easiest to manage line of SBCs on the market. Sangoma's Vega Enterprise SBC provides full-featured protection and easy interconnection at the edge of enterprise networks.

Transforming Cloud Connectivity & Security in Distributed Networks
Today’s digital transformation initiatives frequently begin with moving applications and data to the cloud. But traditional networking and security infrastructure, such as backhauling data from remote locations to central offices over MPLS lines, can’t keep up.
Fortunately, new approaches that also move connectivity and security to the cloud are rapidly overcoming these hurdles. Technologies such as direct-to-cloud SD-WAN and site-to-site VPNs dramatically cut the cost of connectivity. However, they put pressure on other parts of the organization to adopt new ways of defending each site against internet intruders, protecting the use of web content, and securing data stored in cloud apps.
In this webcast, we’ll discuss a new, integrated approach to connectivity and security. Used by enterprises and government agencies around the world to manage as many as 1,500 sites from a single console, Forcepoint’s branch security